spre-sre/lumino-mcp-server

Overview

A diagnostic engine for SRE observability on Konflux and OpenShift. It uses the Model Context Protocol and 40+ tools to analyze logs, metrics, and traces. The tool enables automated root cause analysis and predictive analysis.

Best for

Best for
SRE teams working with Konflux and OpenShift who need automated diagnostics

Use cases

• Automated root cause analysis from observability data
• Predictive analysis of system failures
• Integrating with Konflux and OpenShift monitoring stacks

How to use

Install

pip install -e .

Tools exposed

• KUBERNETES_NAMESPACE
• K8S_NAMESPACE
• PROMETHEUS_URL
• LOG_LEVEL
• MCP_SERVER_LOG_LEVEL
• KUBEARCHIVE_HOST
• KUBEARCHIVE_ENABLED
• THANOS_URL
• PROMETHEUS_TOKEN
• OPENSHIFT_TOKEN
• OC_TOKEN
• log_samples
• failure_labels
• log_failure_correlations
• training_runs
• list_namespaces
• list_pods_in_namespace
• get_kubernetes_resource
• search_resources_by_labels
• query_kubearchive

Tested with

Claude Desktop, Claude Code, Cursor

Notes

A diagnostic engine for SRE observability on Konflux and OpenShift. It uses the Model Context Protocol and 40+ tools to analyze logs, metrics, and traces. The tool enables automated root cause analysis and predictive analysis.

6 stars on GitHub. Last updated 2026-05-21. Licensed Apache-2.0.

Use cases

• Automated root cause analysis from observability data
• Predictive analysis of system failures
• Integrating with Konflux and OpenShift monitoring stacks

Pros

• Uses Model Context Protocol for standardized context handling
• Offers 40+ tools for comprehensive log, metric, and trace analysis
• Python-based, easy to integrate into existing workflows

Cons

• Low GitHub stars (6) indicate early stage or limited adoption
• Requires Konflux and OpenShift environments
• May have limited documentation or community support

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.